카오스 신경망을 이용한 배전계통 최적 구성

Chaotic Neural Networks for Optimal Reconfiguration in Distribution Systems

This paper presents a chaotic neural networks to solve the distribution feeder reconfiguration problem for loss reduction. Feeder reconfiguration problem is the determination of switching option that minimizes the power losses for a particular set of loads in distribution systems. A chaotic neural networks is used to determine the switching combinations, select the status of the switches, and find the best combination of switches for minimum loss. The proposed method has been tested on 32 bus system, and the results indicate that it is able to determine the appropriate switching options for optimal configuration.